A method for automatic cancellation of accident markers

Abstract

The application provides an accident mark automatic cancellation method, and specifically comprises the following steps: performing accident level determination; determining whether to start a power consumption control mode according to the accident level; continuously monitoring the accident vehicle state; determining whether to control the global positioning system module to perform displacement sensing according to the accident vehicle state; performing data packaging according to the data result of displacement sensing and sending the data to the cloud; the cloud receives the data packet and starts a verification mechanism; and determining whether to perform an accident mark cancellation operation according to the verification result. The application solves the problem of lagging accident mark cancellation and waste of vehicle energy in the prior art.

Description

Technical Field

[0001] This invention relates to the field of intelligent transportation technology, and more specifically, to a method for automatically canceling accident markers. Background Technology

[0002] In existing technologies, the cancellation of traffic accident markers mainly relies on the following three methods: Manual intervention: Users or traffic management personnel submit appeals through online platforms or offline windows, relying on manual review of evidence materials. This process can take several days, is inefficient, and has a low success rate. Static time threshold: Navigation platforms automatically cancel markers after setting a fixed time interval, but they cannot perceive the accident clearance status in real time, making them prone to accidental cancellation or delays. Basic displacement determination: Some high-end intelligent connected vehicles trigger cancellation through GPS displacement monitoring, but this has problems such as high energy consumption and weak scene adaptability.

[0003] Accident marker cancellation is too delayed, causing drivers to take ineffective detours and find no accident upon arrival; or the vehicle's GPS continues to operate at full power after an accident, resulting in wasted vehicle energy. Summary of the Invention

[0004] The problem solved by this invention is that the cancellation of accident markers is delayed in the prior art, which wastes vehicle energy.

[0005] To address the aforementioned problems, this invention provides a method for automatically canceling accident markers. The method includes the following steps: performing an accident level determination; determining whether to activate a power consumption control mode based on the accident level; continuously monitoring the status of the accident vehicle; determining whether to control the global positioning system module to perform displacement sensing based on the accident vehicle status; packaging and sending the data to the cloud based on the displacement sensing data results; receiving the data packet and initiating a verification mechanism in the cloud; and determining whether to perform an accident marker cancellation operation based on the verification results.

[0006] Compared to existing technologies, the technical effects achieved by this solution are as follows: The automatic accident marker cancellation method, by performing accident level determination, can adopt different handling strategies based on the severity of the accident. Combined with whether to activate the power consumption control mode, it can reasonably control energy consumption while ensuring monitoring effectiveness and avoiding resource waste. Continuous monitoring of the accident vehicle's status and determining whether to control the GPS module to perform displacement sensing based on the status can accurately capture the vehicle's actual movement, providing a reliable basis for subsequent operations. The cloud-based verification mechanism, which determines whether to cancel the accident marker based on the result, automates and intelligently cancels the accident marker, reducing manual intervention, improving the efficiency and accuracy of accident handling, ensuring that the accident marker matches the actual vehicle status, and avoiding misjudgments or omissions.

[0007] Furthermore, the accident level determination process includes the following steps: setting acceleration trigger thresholds, trigger time, pressure thresholds, difference thresholds, and suspension displacement thresholds; detecting triaxial acceleration, airbag pressure values, and suspension displacement; if the Z-axis acceleration exceeds the acceleration trigger threshold within the trigger time, it is determined to be a primary accident; if the airbag pressure value exceeds the pressure threshold and the difference between multiple airbag pressure values ​​measured by the sensors is less than the difference threshold, it is confirmed as a valid trigger; if the suspension displacement exceeds the suspension displacement threshold, it is determined to be valid evidence of physical deformation; calculating the accident index based on the maximum value of the triaxial acceleration, the average value of multiple airbag pressure values, and the suspension displacement; and determining whether the accident is a moderate or severe accident based on the accident index.

[0008] Compared to existing technologies, this technical solution achieves the following advantages: In practical applications, primary accidents cause minimal vehicle damage and are easy to handle; the vehicle can often leave the scene on its own without needing to mark the accident or require external assistance. However, in moderate accidents, airbags often deploy, resulting in changes in airbag pressure and a higher maximum value for the vehicle's three-axis acceleration compared to primary accidents. In such cases, occupants may be unable to continue driving or take further action, and the vehicle may remain immobile for a certain period. By setting multiple specific thresholds, such as acceleration trigger thresholds and pressure thresholds, clear quantitative standards are provided for accident severity assessment. Combining this with airbag pressure values ​​to determine effective triggering avoids false alarms. In more severe collisions, in addition to three-axis acceleration and airbag data, the vehicle often experiences suspension deformation and displacement. Including suspension displacement in the accident severity assessment, and calculating an accident index to determine moderate or severe accidents, further improves the accuracy of accident severity assessment. This provides a scientific basis for subsequent operations such as activating power consumption control modes, ensuring that the handling measures match the severity of the accident.

[0009] Furthermore, determining whether to activate the power consumption control mode based on the accident level includes the following steps: if the accident is determined to be moderate, then the power consumption control mode is activated; the power consumption control mode includes: reducing the power consumption of the vehicle positioning unit; reducing the sampling frequency of the inertial measurement unit and setting the vibration detection threshold; and shutting down secondary loads.

[0010] Compared to existing technologies, this technical solution achieves the following advantages: Reduced power consumption of the vehicle positioning unit and sampling frequency of the inertial measurement unit (IMU) allow for reduced energy consumption while maintaining core monitoring functions, extending the vehicle's power supply life after an accident and preventing the loss of critical data or monitoring interruption due to power depletion. Setting a vibration detection threshold ensures that the IMU can effectively capture critical vibration signals even at low sampling frequencies, without affecting subsequent vehicle status assessments. Disabling secondary loads further reduces unnecessary energy consumption, concentrating limited energy for core monitoring and communication functions, thus improving the stability and continuity of system operation during accident handling.

[0011] Furthermore, determining whether to control the GPS module to perform displacement sensing based on the condition of the accident vehicle specifically includes the following steps: when the inertial measurement unit detects a continuous vibration characteristic that exceeds the vibration detection threshold, the system controls the GPS module to perform displacement sensing.

[0012] Compared with existing technologies, the technical effects achieved by this solution are as follows: vibration characteristics serve as a precursor signal for possible vehicle displacement, which is used as a condition to trigger the operation of the GPS module. This allows for accurate capture of the vehicle's displacement status, ensuring that displacement data is obtained in a timely manner through the GPS module when the vehicle is actually moving. This provides an accurate basis for the subsequent verification of accident marker cancellation, ensuring both the effectiveness of monitoring and reasonable control of energy consumption.

[0013] Furthermore, displacement sensing specifically includes the following steps: setting a dynamic threshold benchmark value according to the road type and making dynamic corrections based on environmental parameters; collecting the original coordinate points of the accident vehicle and eliminating multipath effect errors; mapping the vehicle coordinates to the lane centerline through a road projection algorithm; and calculating the surface distance using the semi-versus formula based on the World Geodetic System ellipsoid model.

[0014] Compared to existing technologies, this technical solution achieves the following effects: By setting dynamic threshold benchmarks based on road type and adjusting for environmental parameters, the standard for displacement judgment better reflects actual road conditions, improving the adaptability and accuracy of the threshold. After collecting original coordinate points, multipath effects are eliminated, reducing interference from factors such as signal reflection on positioning accuracy and ensuring the authenticity of coordinate data. By mapping coordinates to lane centerlines using a road projection algorithm, the representation of vehicle position more accurately reflects the actual road layout, facilitating accurate judgment of vehicle displacement within the road. Based on the World Geodetic System ellipsoidal model, the semi-versus formula is used to calculate surface distances, taking into account the Earth's surface curvature. This method is more accurate than planar distance calculations, truly reflecting the actual displacement of vehicles and providing a reliable quantitative basis for subsequent data analysis.

[0015] Furthermore, based on the displacement sensing data results, data packaging is performed and sent to the cloud. Specifically, if the surface distance exceeds the dynamic threshold reference value within the set detection window, data packaging is performed and sent to the cloud.

[0016] Compared to existing technologies, this technical solution achieves the following advantages: By setting a detection window and using a surface distance exceeding a dynamic threshold as the trigger condition for data packet transmission, invalid data transmission caused by minor vehicle vibrations or other non-substantial displacements is avoided, reducing cloud-based data processing and communication energy consumption. Data is only transmitted when the vehicle displacement reaches a certain level, ensuring the data uploaded to the cloud has practical significance, improving the effectiveness and relevance of data transmission, providing valuable judgment criteria for the cloud verification mechanism, and optimizing system communication efficiency.

[0017] Furthermore, the specific steps of the verification mechanism include: verifying the spatiotemporal continuity of the data; performing collaborative verification of the trajectories of surrounding vehicles; excluding no-parking zones; and writing the hash value of the data into the smart contract.

[0018] Compared to existing technologies, this technical solution achieves the following effects: Verifying the spatiotemporal continuity of data ensures that uploaded displacement data is consistent and reasonable in time and space, avoiding misjudgments caused by data anomalies or tampering. Performing collaborative verification of surrounding vehicle trajectories enhances the credibility of displacement judgment through cross-comparison of multi-vehicle data, reducing potential errors from single-vehicle data. Excluding no-stopping zones avoids misjudging abnormal vehicle displacement within these zones as valid movement, improving the rationality of verification. Writing the data's hash value into a smart contract leverages the immutability of blockchain technology to guarantee data integrity and security, preventing data tampering during transmission or storage, ensuring the reliability of verification results, and thus making the accident marker cancellation operation more credible and accurate.

[0019] Furthermore, determining whether to perform the accident marker cancellation operation based on the verification results includes the following steps: If the verification mechanism passes, the accident marker cancellation operation is performed; the accident marker cancellation operation includes the following steps: updating the traffic information on the navigation platform; synchronizing the traffic management system status, and completing the accident marker cancellation operation.

[0020] Compared to existing technologies, this technical solution achieves the following effects: Accident marker cancellation is performed only after the verification mechanism is passed, ensuring operational accuracy and preventing accidental cancellations from impacting traffic management. Updating navigation platform traffic information allows for timely feedback of accident processing status to other vehicles, guiding them to plan routes rationally and reducing traffic congestion caused by unresolved accident markers. Synchronizing the traffic management system status enables traffic management departments to monitor accident processing progress in real time, facilitating subsequent traffic control and management, and improving the collaborative efficiency of accident handling.

[0021] Furthermore, before the step of continuously monitoring the status of the accident vehicle, and after determining whether to activate the power consumption control mode based on the accident level, the method for automatically canceling the accident marker also includes: activating the sleep mode when the vehicle battery voltage is lower than a set threshold. In the sleep mode, the system power consumption only maintains the near-field communication wake-up circuit in standby mode.

[0022] Compared to existing technologies, the technical advantages achieved by this solution are: maintaining the near-field communication wake-up circuit in standby mode minimizes system power consumption, extends battery life, and prevents the vehicle from completely losing its monitoring and communication capabilities due to power depletion. The standby setting of the near-field communication wake-up circuit allows the vehicle to be woken up by external signals even in sleep mode, facilitating subsequent vehicle processing or system reactivation, and ensuring basic interactivity of the vehicle in low-battery conditions.

[0023] Furthermore, in hibernation mode, the last known location of the accident vehicle is transmitted via satellite at regular intervals.

[0024] Compared to existing technologies, this technical solution achieves the following advantages: During sleep mode, the last known location of the accident vehicle is transmitted via satellite at regular intervals. This not only provides relevant parties with approximate vehicle location information in a low-power state, facilitating vehicle tracking by rescue personnel, traffic management departments, or vehicle owners and preventing vehicle loss, but also saves more power compared to continuous transmission. This balances the need for location information updates with energy consumption control, ensuring effective transmission of location information as much as possible with limited power. Attached Figure Description

[0025] Figure 1 A flowchart of an automatic accident marker cancellation method provided by the present invention;

[0026] Figure 2 Flowchart for accident level determination;

[0027] Figure 3 The flowchart for verifying the mechanism execution. Detailed Implementation

[0028] The purpose of this invention is to provide an automatic accident marker cancellation method, which improves the accuracy and efficiency of accident marker cancellation and saves vehicle energy consumption.

[0029] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0030] See Figures 1-2This invention provides a method for automatically canceling accident markers. The method includes the following steps: performing an accident level determination; determining whether to activate a power consumption control mode based on the accident level; continuously monitoring the status of the accident vehicle; determining whether to control the global positioning system module to perform displacement sensing based on the status of the accident vehicle; packaging data and sending it to the cloud based on the displacement sensing data results; receiving the data packet and initiating a verification mechanism in the cloud; and determining whether to perform an accident marker cancellation operation based on the verification results.

[0031] The automatic accident marker cancellation method, by performing accident level determination, can adopt different handling strategies according to the severity of the accident. Combined with whether to activate the power consumption control mode, it can reasonably control energy consumption while ensuring monitoring effectiveness and avoiding resource waste. Continuously monitoring the status of the accident vehicle and determining whether to control the GPS module to perform displacement sensing based on the status can accurately capture the actual movement of the vehicle and provide reliable data for subsequent operations. The cloud-based verification mechanism determines whether to cancel the accident marker based on the result, realizing the automation and intelligence of accident marker cancellation, reducing manual intervention, improving the efficiency and accuracy of accident handling, ensuring that the accident marker matches the actual vehicle status, and avoiding misjudgment or omission.

[0032] The accident severity determination process includes the following steps: setting acceleration trigger thresholds, trigger time, pressure thresholds, difference thresholds, and suspension displacement thresholds; detecting triaxial acceleration, airbag pressure values, and suspension displacement; if the Z-axis acceleration exceeds the acceleration trigger threshold within the trigger time, it is determined to be a primary accident; if the airbag pressure value exceeds the pressure threshold and the difference between multiple airbag pressure values ​​measured by the sensors is less than the difference threshold, it is confirmed as a valid trigger; if the suspension displacement exceeds the suspension displacement threshold, it is determined to be valid evidence of physical deformation; calculating the accident index based on the maximum value of the triaxial acceleration, the average value of multiple airbag pressure values, and the suspension displacement; and determining whether the accident is a moderate or severe accident based on the accident index.

[0033] Specifically, in this embodiment, a triaxial accelerometer with a sampling frequency of 100Hz is used to detect the triaxial acceleration of the vehicle, a dual-channel airbag pressure sensor with a range of 0 to 50 psi is used to detect the airbag pressure value, and a laser suspension displacement monitor with an accuracy of ±0.1 mm is used to detect the suspension displacement.

[0034] In this embodiment, the trigger time is set to 50ms and the acceleration trigger threshold is set to 5g (where g refers to gravitational acceleration). That is, if the Z-axis acceleration exceeds the 5g threshold for 50ms, the primary accident judgment is triggered.

[0035] The pressure threshold is set to 30 psi, and the difference threshold is set to 5%. That is, if the airbag pressure value exceeds 30 psi and the difference between multiple airbag pressure values ​​measured by the sensor is less than 5%, it will be determined as a valid trigger.

[0036] The suspension displacement threshold is set at 15mm, meaning that if the suspension displacement exceeds 15mm, it is considered valid evidence of physical deformation.

[0037] In this embodiment, the accident index is defined as Q;

[0038] The calculation formula is Q=0.6×G. max +0.3×P avg +0.1×D dis ;

[0039] Among them, G max P represents the maximum acceleration detected by the triaxial accelerometer during a vehicle collision. avg D is the average value of the airbag pressure values ​​from the dual-channel airbag pressure sensor. dis The value represents the suspension displacement. The coefficient before the physical quantity indicates the weight of that physical quantity in the accident index. For example, the instantaneous acceleration of a vehicle collision can intuitively reflect the impact intensity and is the most direct indicator for judging the severity of an accident, so the weight coefficient is 0.6.

[0040] Based on the aforementioned calculation formula, when 6 < Q ≤ 8, the accident is determined to be a moderate accident; when Q > 8, the accident is determined to be a severe accident.

[0041] In practical applications, primary accidents cause minimal vehicle damage and are easy to handle; the occupants may even be able to leave the scene on their own without needing to mark the accident or have external personnel intervene. However, in moderate accidents, airbags often deploy, resulting in changes in airbag pressure and a higher maximum value for the vehicle's three-axis acceleration compared to primary accidents. In such cases, occupants may be unable to continue driving or take further action due to various reasons, and the vehicle may remain immobile for a certain period. By setting multiple specific thresholds, such as acceleration trigger thresholds and pressure thresholds, clear quantitative standards are provided for accident severity assessment. Combining this with airbag pressure values ​​to determine effective triggering avoids false alarms. In more severe collisions, in addition to three-axis acceleration and airbag data, the vehicle often exhibits some degree of suspension deformation and displacement. Including suspension displacement in the accident severity assessment, and calculating an accident index to determine whether an accident is moderate or severe, further improves the accuracy of accident severity assessment. This provides a scientific basis for subsequent operations such as activating power consumption control modes, ensuring that the handling measures match the severity of the accident.

[0042] Determining whether to activate the power consumption control mode based on the accident level includes the following steps: If the accident is determined to be moderate, the power consumption control mode is activated; the power consumption control mode includes: reducing the power consumption of the vehicle positioning unit; reducing the sampling frequency of the inertial measurement unit and setting the vibration detection threshold; and shutting down secondary loads.

[0043] Specifically, the power consumption of the vehicle positioning unit is reduced so that it is only used to maintain the operation of the basic clock circuit; the sampling frequency of the inertial measurement unit is reduced from 100Hz to 10Hz; the vibration detection threshold is set to 0.3g; and secondary loads include the vehicle entertainment system and ambient lighting.

[0044] Reducing the power consumption of the vehicle positioning unit and the sampling frequency of the inertial measurement unit (IMU) can reduce energy consumption while ensuring core monitoring functions, extend the vehicle's power supply range after an accident, and prevent the loss of critical data or monitoring interruption due to power depletion. Setting a vibration detection threshold ensures that the IMU can still effectively capture critical vibration signals at low sampling frequencies, without affecting subsequent judgments of the vehicle's status. Disabling secondary loads further reduces unnecessary energy consumption, concentrating limited energy on core monitoring and communication functions, thus improving the stability and continuity of system operation during accident handling.

[0045] Determining whether to control the GPS module to perform displacement sensing based on the condition of the accident vehicle includes the following steps: When the inertial measurement unit detects a continuous vibration feature that exceeds the vibration detection threshold, the system controls the GPS module to perform displacement sensing.

[0046] Specifically, when the inertial measurement unit detects a vibration characteristic exceeding 0.3g for more than 200ms, the system controls the global positioning system module to perform displacement sensing.

[0047] Vibration characteristics serve as a precursor signal for potential vehicle displacement. This signal triggers the operation of the GPS module, enabling precise capture of the vehicle's displacement status. It ensures timely acquisition of displacement data via the GPS module when the vehicle is actually moving, providing accurate evidence for subsequent verification of accident marker cancellation. This approach guarantees the effectiveness of monitoring while also achieving reasonable energy consumption control.

[0048] Displacement sensing specifically includes the following steps: setting a dynamic threshold benchmark value according to the road type and making dynamic corrections based on environmental parameters; collecting the original coordinate points of the accident vehicle and eliminating multipath effect errors; mapping the vehicle coordinates to the lane centerline using a road projection algorithm; and calculating the surface distance using the semi-versus formula based on the World Geodetic System ellipsoid model.

[0049] Specifically, the original coordinate point sampling rate is 1Hz. A Kalman filter is used to eliminate multipath error. The model used to calculate the surface distance is the WGS84 ellipsoid model.

[0050] In this embodiment, the dynamic threshold benchmark value for urban roads is 30 meters, the dynamic threshold benchmark value for highways is 200 meters, and the dynamic threshold benchmark value for underground parking garages is 15 meters. Specifically, the dynamic correction includes increasing the curvature compensation coefficient by (100 / R)% when the radius of a curve is less than 100 meters, and applying an attenuation factor of 0.6-0.8 in rainy or snowy weather.

[0051] By setting dynamic threshold benchmarks based on road type and adjusting them in conjunction with environmental parameters, the displacement judgment standard is made more closely aligned with actual road conditions, improving the adaptability and accuracy of the thresholds. After collecting the original coordinate points, multipath effects are eliminated, reducing interference from factors such as signal reflection on positioning accuracy and ensuring the authenticity of the coordinate data. A road projection algorithm maps the coordinates to the lane centerline, making the representation of vehicle position more consistent with the actual road layout, facilitating accurate judgment of vehicle displacement within the road. Based on the World Geodetic System ellipsoidal model, the semi-versus formula is used to calculate surface distances, taking into account the Earth's surface curvature. This method is more accurate than planar distance calculations and can truly reflect the actual displacement of vehicles, providing a reliable quantitative basis for subsequent data interpretation.

[0052] Based on the displacement sensing data results, data is packaged and sent to the cloud. Specifically, if the surface distance exceeds the dynamic threshold reference value within the set detection window, data is packaged and sent to the cloud.

[0053] The detection window is set to 120 seconds.

[0054] By setting a detection window and using a surface distance exceeding a dynamic threshold as the trigger condition for data packet transmission, invalid data transmission caused by non-substantial displacements such as minor vehicle swaying is avoided, reducing cloud data processing load and communication energy consumption. Data is only sent when the vehicle displacement reaches a certain level, ensuring that the data uploaded to the cloud has practical significance, improving the effectiveness and relevance of data transmission, providing valuable judgment criteria for the cloud verification mechanism, and optimizing the system's communication efficiency.

[0055] See Figure 3 The specific steps of the verification mechanism include: verifying the spatiotemporal continuity of the data; performing collaborative verification of the trajectories of surrounding vehicles; excluding no-parking zones; and writing the hash value of the data into the smart contract.

[0056] Specifically, when the interval between trajectory coordinate points is less than 2 seconds and the displacement difference is less than 50 meters, and the path curvature change rate does not exceed 5° per meter, the spatiotemporal continuity verification is passed.

[0057] Collaborative verification of surrounding vehicle trajectories includes querying the driving records of V2X vehicles within a 300-meter radius, requiring at least one vehicle to report changes in the same location.

[0058] If the verification mechanism fails, a three-level review process is initiated. The first level involves automatic re-verification three times. The second level involves AI analysis of the last 30 seconds of video from the driver monitoring system's camera. The third level involves manual review and judgment by the traffic management platform.

[0059] Verifying the spatiotemporal continuity of the data ensures that the uploaded displacement data is consistent and reasonable in time and space, avoiding misjudgments due to data anomalies or tampering. Performing collaborative verification of surrounding vehicle trajectories enhances the credibility of displacement judgments through cross-comparison of multi-vehicle data, reducing potential errors from single-vehicle data. Excluding no-stopping zones prevents abnormal vehicle displacement within these zones from being misjudged as valid movement, improving the rationality of the verification. Writing the data's hash value into a smart contract leverages the immutability of blockchain technology to guarantee data integrity and security, preventing data tampering during transmission or storage and ensuring the reliability of verification results. This makes the accident marker cancellation operation more credible and accurate.

[0060] Determining whether to perform the accident marker cancellation operation based on the verification results includes the following steps: If the verification mechanism passes, the accident marker cancellation operation is performed; The accident marker cancellation operation includes the following steps: updating the traffic information on the navigation platform; synchronizing the traffic management system status, and completing the accident marker cancellation operation.

[0061] The navigation platform traffic information is updated specifically via a WebSocket long connection within 500ms.

[0062] The synchronized traffic management system status is specifically defined as the synchronized traffic management system status within 3 seconds via the GB / T 26773 standard API gateway.

[0063] Optionally, the cancellation of an accident marker may also include the following steps, which are performed after synchronizing the traffic management system status: pushing an MQ message containing a blockchain certificate to the insurance platform to trigger automatic claims processing; the user terminal simultaneously receives a notification from the in-vehicle voice broadcast that the accident marker has been cancelled, the car owner's APP generates a processing report containing a trajectory map and a stored evidence ID, and automatically schedules a 4S store repair service.

[0064] Once the verification mechanism is successful, the accident marker cancellation operation is performed, ensuring the accuracy of the operation and avoiding accidental cancellations that could impact traffic management. Updating traffic information on the navigation platform allows for timely feedback of the accident's status to other vehicles, guiding them to plan routes rationally and reducing traffic congestion caused by unresolved accident markers. Synchronizing the traffic management system status enables traffic management departments to monitor the accident handling progress in real time, facilitating subsequent traffic control and management efforts and improving the collaborative efficiency of accident handling.

[0065] Before continuously monitoring the status of the accident vehicle, and after determining whether to activate the power consumption control mode based on the accident level, the automatic cancellation method for accident markers also includes: activating a sleep mode when the vehicle battery voltage is lower than a set threshold. In the sleep mode, the system power consumption only maintains the near-field communication wake-up circuit in standby mode.

[0066] Specifically, the vehicle battery voltage setting threshold is 11.8V.

[0067] Maintaining only the near-field communication wake-up circuit in standby mode minimizes system power consumption, extends battery life, and prevents the vehicle from completely losing its monitoring and communication capabilities due to depleted battery power. The standby setting of the near-field communication wake-up circuit allows the vehicle to be woken up by external signals even in sleep mode, facilitating subsequent vehicle processing or system reactivation, and ensuring basic interactivity when the vehicle is low on battery power.

[0068] In hibernation mode, the last known location of the accident vehicle is transmitted via satellite at regular intervals.

[0069] Preferably, the interval is 30 minutes.

[0070] In sleep mode, the system transmits the last known location of the accident vehicle via satellite at regular intervals. This allows for continuous provision of approximate vehicle location information to relevant parties while maintaining low power consumption, facilitating vehicle tracking by rescue personnel, traffic management departments, or vehicle owners and preventing vehicle loss. Furthermore, the interval transmission method is more energy-efficient than continuous transmission, balancing the need for location information updates with energy consumption control, and ensuring effective transmission of location information as much as possible with limited power.

[0071] In summary, this invention can significantly optimize the accuracy and efficiency of accident marker cancellation, avoid unnecessary detours for other vehicles, significantly reduce the power consumption of the accident vehicle after the accident, extend the battery's range, and encode the hash value into a smart contract to form an immutable electronic certificate, providing reliable technical support for modern traffic management.

[0072] While the present invention has been disclosed above, it is not limited thereto. Any person skilled in the art can make various modifications and alterations without departing from the spirit and scope of the invention; therefore, the scope of protection of the present invention should be determined by the scope defined in the claims.

Claims

1. An automatic cancellation method of an accident marker, characterized by, The accident mark automatic cancellation method comprises the following steps: Performing accident level determination; Judging whether to start power consumption control mode according to the accident level; Continuously monitoring the accident vehicle state; Judging whether to control the global positioning system module to perform displacement sensing according to the accident vehicle state; Performing data packaging and sending to the cloud according to the data result of displacement sensing; The cloud receives the data package and starts the verification mechanism; Judging whether to perform the accident mark cancellation operation according to the verification result.

2. The method of claim 1, wherein, The accident level determination comprises the following steps: Setting acceleration trigger threshold, trigger time, pressure threshold, difference threshold, and suspension displacement threshold; Detecting three-axis acceleration, airbag pressure value, and suspension displacement amount; If the Z-axis acceleration exceeds the acceleration trigger threshold within the trigger time, it is determined to be a primary accident; If the airbag pressure value exceeds the pressure threshold and the difference between multiple airbag pressure values measured by the sensor is less than the difference threshold, it is determined to be a valid trigger; If the suspension displacement amount exceeds the suspension displacement threshold, it is determined to be valid physical deformation evidence; Calculating an accident index according to the maximum value of the three-axis acceleration, the average value of multiple airbag pressure values, and the suspension displacement amount; Determining whether the accident is a moderate accident or a severe accident according to the accident index.

3. The method of claim 2, wherein, The judgment of whether to start power consumption control mode according to the accident level comprises the following steps: If it is determined to be a moderate accident, the power consumption control mode is started; The power consumption control mode comprises: Reducing the power consumption of the vehicle positioning unit; Reducing the sampling frequency of the inertial measurement unit and setting a vibration detection threshold; Turning off the secondary load.

4. The method of claim 3, wherein, The judgment of whether to control the global positioning system module to perform displacement sensing according to the accident vehicle state comprises the following steps: When the inertial measurement unit detects continuous vibration characteristics that exceed the vibration detection threshold, the system controls the global positioning system module to perform displacement sensing.

5. The method of claim 1, wherein, The displacement sensing comprises the following steps: Setting a dynamic threshold reference value according to the road type and dynamically correcting it according to environmental parameters; Collecting the original coordinate points of the accident vehicle and eliminating multipath effect errors; Mapping the vehicle coordinates to the lane center line through road projection algorithm; Calculating the curved surface distance based on the World Geodetic System ellipsoid model using the subtangent formula.

6. The method of claim 5, wherein, The data packaging and sending to the cloud according to the data result of displacement sensing specifically comprises: if the curved surface distance exceeds the dynamic threshold reference value within the set detection window, performing data packaging and sending to the cloud.

7. The method of claim 6, wherein, The verification mechanism specifically comprises the following steps: Verifying the spatiotemporal continuity of the data; Performing surrounding vehicle trajectory collaborative verification; Excluding prohibited parking areas; Writing the hash value of the data into a smart contract.

8. The method of claim 1, wherein, The judgment of whether to perform the accident mark cancellation operation according to the verification result comprises the following steps: If the verification mechanism passes, the accident mark cancellation operation is performed; The accident mark cancellation operation comprises the following steps: Updating the navigation platform road condition information; Synchronizing the traffic management system state to complete the accident mark cancellation operation.

9. The automatic cancellation method of an accident marker according to any one of claims 1 to 8, characterized by, Before the step of continuously monitoring the state of the accident vehicle, after the step of determining whether to start the power consumption control mode according to the accident level, the automatic accident marking cancellation method further comprises: starting a hibernation mode when the vehicle battery voltage is lower than a set threshold, in the hibernation mode, the system power consumption only maintains the standby of the near field communication wake-up circuit.

10. The method of claim 9, wherein, In the hibernation mode, the last known position of the accident vehicle is sent through a satellite every certain time interval.

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